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Assessment of Above-Ground Biomass of Borneo Forests through a New Data-Fusion Approach Combining Two Pan-Tropical Biomass Maps

Author

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  • Andreas Langner

    (European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via E. Fermi, 2749, I-21027 Ispra (VA), Italy)

  • Frédéric Achard

    (European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via E. Fermi, 2749, I-21027 Ispra (VA), Italy)

  • Christelle Vancutsem

    (European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via E. Fermi, 2749, I-21027 Ispra (VA), Italy)

  • Jean-Francois Pekel

    (European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via E. Fermi, 2749, I-21027 Ispra (VA), Italy)

  • Dario Simonetti

    (European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via E. Fermi, 2749, I-21027 Ispra (VA), Italy)

  • Giacomo Grassi

    (European Commission, Joint Research Centre, Institute for Environment and Sustainability, Via E. Fermi, 2749, I-21027 Ispra (VA), Italy)

  • Kanehiro Kitayama

    (Graduate School of Agriculture, Kyoto University, Oiwake-cho, Kitashirakawa, Sakyo-ku, Kyoto 606-8502, Japan)

  • Mikiyasu Nakayama

    (Department of International Studies, Graduate School of Frontier Science, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba 277-8563, Japan)

Abstract

This study investigates how two existing pan-tropical above-ground biomass (AGB) maps (Saatchi 2011, Baccini 2012) can be combined to derive forest ecosystem specific carbon estimates. Several data-fusion models which combine these AGB maps according to their local correlations with independent datasets such as the spectral bands of SPOT VEGETATION imagery are analyzed. Indeed these spectral bands convey information about vegetation type and structure which can be related to biomass values. Our study area is the island of Borneo. The data-fusion models are evaluated against a reference AGB map available for two forest concessions in Sabah. The highest accuracy was achieved by a model which combines the AGB maps according to the mean of the local correlation coefficients calculated over different kernel sizes. Combining the resulting AGB map with a new Borneo land cover map (whose overall accuracy has been estimated at 86.5%) leads to average AGB estimates of 279.8 t/ha and 233.1 t/ha for forests and degraded forests respectively. Lowland dipterocarp and mangrove forests have the highest and lowest AGB values (305.8 t/ha and 136.5 t/ha respectively). The AGB of all natural forests amounts to 10.8 Gt mainly stemming from lowland dipterocarp (66.4%), upper dipterocarp (10.9%) and peat swamp forests (10.2%). Degraded forests account for another 2.1 Gt of AGB. One main advantage of our approach is that, once the best fitting data-fusion model is selected, no further AGB reference dataset is required for implementing the data-fusion process. Furthermore, the local harmonization of AGB datasets leads to more spatially precise maps. This approach can easily be extended to other areas in Southeast Asia which are dominated by lowland dipterocarp forest, and can be repeated when newer or more accurate AGB maps become available.

Suggested Citation

  • Andreas Langner & Frédéric Achard & Christelle Vancutsem & Jean-Francois Pekel & Dario Simonetti & Giacomo Grassi & Kanehiro Kitayama & Mikiyasu Nakayama, 2015. "Assessment of Above-Ground Biomass of Borneo Forests through a New Data-Fusion Approach Combining Two Pan-Tropical Biomass Maps," Land, MDPI, vol. 4(3), pages 1-14, August.
    • Handle: RePEc:gam:jlands:v:4:y:2015:i:3:p:656-669:d:53660
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    References listed on IDEAS

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    1. A. Baccini & S. J. Goetz & W. S. Walker & N. T. Laporte & M. Sun & D. Sulla-Menashe & J. Hackler & P. S. A. Beck & R. Dubayah & M. A. Friedl & S. Samanta & R. A. Houghton, 2012. "Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps," Nature Climate Change, Nature, vol. 2(3), pages 182-185, March.
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